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All Journal Jurnal Ilmiah Multidisiplin Amsir
Eddy, Hadryan
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Religion Economics, Econometrics & Finance Law, Crime, Criminology & Criminal Justice Public Health Other

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Implementasi Kecerdasan Buatan pada Metode Pembelajaran Tingkat Universitas di Era Persaingan LLM Open Source dan Closed Source (2023–2025): Tinjauan Sistematis Eddy, Hadryan; Hidayatullah, Muhammad Dimas
Jurnal Ilmiah Multidisiplin Amsir Vol 4 No 1 (2025): Desember
Publisher : AhInstitute of Research and Community Service (LP2M) Institute of Social Sciences and Business Andi Sapada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62861/jimat amsir.v4i1.720

Abstract

Periode 2023 hingga 2025 menandai titik balik kritis dalam ekosistem pendidikan tinggi, di mana kecerdasan buatan (AI) bertransformasi dari sekadar objek kajian akademik menjadi infrastruktur pembelajaran yang melekat dalam keseharian sivitas akademika. Studi ini menyajikan tinjauan sistematis berprotokol PRISMA yang mensintesis 47 sumber primer, mencakup survei UNESCO, meta-analisis jurnal terindeks Scopus dan Web of Science, serta data empiris dari perguruan tinggi Indonesia. Tujuan utamanya adalah mendekonstruksi realitas adopsi AI melampaui statistik permukaan, menuju pemahaman mendalam tentang dinamika pedagogis dan tata kelola institusi. Temuan mengonfirmasi lonjakan adopsi AI di kalangan mahasiswa dari 27% (2023) menjadi 92% (2025), dengan dampak positif terukur pada capaian kognitif (effect size d=0,94). Namun, terdapat paradoks kebijakan yang mengkhawatirkan: hanya 19% institusi secara global dan sekitar 20% dari 15 universitas terkemuka di Indonesia yang memiliki regulasi AI formal. Situasi ini semakin kompleks akibat persaingan intensif antara model LLM open source dan closed source yang mereduksi relevansi regulasi berbasis nama alat. Merespons kesenjangan tersebut, penelitian ini mengartikulasikan Kerangka PAIR (Policy–Access–Integrity–Readiness) sebagai panduan strategis untuk mewujudkan adopsi AI yang bertanggung jawab dan kontekstual dalam pendidikan tinggi Indonesia.
Implementation of K-means and Weight Product (WP) Methods in Determining Work From Home (WFH) Priorities in the New Normal Period in Indonesia Eddy, Hadryan
Jurnal Ilmiah Multidisiplin Amsir Vol. 3 No. 1 (2024): Desember
Publisher : AhInstitute of Research and Community Service (LP2M) Institute of Social Sciences and Business Andi Sapada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62861/jimat.v3i1.849

Abstract

Covid-19 (SARS-CoV-2) is a new type of virus that began in the city of Wuhan, China in late 2019. Over time, the development of the Covid -19 Virus has greatly increased so that it has an overall impact on an organization. Currently, there are various methods in organizations that have been carried out to reduce the development of COVID-19, one of which is working from home during the New Normal period. This research aims to apply the K-Means and Weight Product (WP) methods in determining the priority of giving WFH schedules to all employees depending on the conditions of each employee. The K-Means method is used to group a number of covid-19 patient case data based on age and disease history. The output results of the process will be used as input criteria and criteria importance in the WP method. The use of the Elbow method makes it easy to determine the value of K in the clustering process on various data used. In this study, the best K value is 3 based on the evaluation results using the elbow method. The use of 2 criteria from the results of clustering covid-19 patient data in making decision models with the WP method provides more objective and precise decision results based on data / facts that have occurred. The functionality aspect of the system is very good after going through the process of testing the calculation results manually and using the system, both have the same results.
Implementation of K-means and Weight Product (WP) Methods in Determining Work From Home (WFH) Priorities in the New Normal Period in Indonesia Eddy, Hadryan
Jurnal Ilmiah Multidisiplin Amsir Vol. 3 No. 1 (2024): Desember
Publisher : AhInstitute of Research and Community Service (LP2M) Institute of Social Sciences and Business Andi Sapada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62861/jimat.v3i1.866

Abstract

Covid-19 (SARS-CoV-2) is a new type of virus that began in the city of Wuhan, China in late 2019. Over time, the development of the Covid -19 Virus has greatly increased so that it has an overall impact on an organization. Currently, there are various methods in organizations that have been carried out to reduce the development of COVID-19, one of which is working from home during the New Normal period. This research aims to apply the K-Means and Weight Product (WP) methods in determining the priority of giving WFH schedules to all employees depending on the conditions of each employee. The K-Means method is used to group a number of covid-19 patient case data based on age and disease history. The output results of the process will be used as input criteria and criteria importance in the WP method. The use of the Elbow method makes it easy to determine the value of K in the clustering process on various data used. In this study, the best K value is 3 based on the evaluation results using the elbow method. The use of 2 criteria from the results of clustering covid-19 patient data in making decision models with the WP method provides more objective and precise decision results based on data / facts that have occurred. The functionality aspect of the system is very good after going through the process of testing the calculation results manually and using the system, both have the same results.
Implementasi Kecerdasan Buatan pada Metode Pembelajaran Tingkat Universitas di Era Persaingan LLM Open Source dan Closed Source (2023–2025): Tinjauan Sistematis Eddy, Hadryan; Hidayatullah, Muhammad Dimas
Jurnal Ilmiah Multidisiplin Amsir Vol. 4 No. 1 (2025): Desember
Publisher : AhInstitute of Research and Community Service (LP2M) Institute of Social Sciences and Business Andi Sapada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62861/jimat.v4i1.902

Abstract

Periode 2023 hingga 2025 menandai titik balik kritis dalam ekosistem pendidikan tinggi, di mana kecerdasan buatan (AI) bertransformasi dari sekadar objek kajian akademik menjadi infrastruktur pembelajaran yang melekat dalam keseharian sivitas akademika. Studi ini menyajikan tinjauan sistematis berprotokol PRISMA yang mensintesis 47 sumber primer, mencakup survei UNESCO, meta-analisis jurnal terindeks Scopus dan Web of Science, serta data empiris dari perguruan tinggi Indonesia. Tujuan utamanya adalah mendekonstruksi realitas adopsi AI melampaui statistik permukaan, menuju pemahaman mendalam tentang dinamika pedagogis dan tata kelola institusi. Temuan mengonfirmasi lonjakan adopsi AI di kalangan mahasiswa dari 27% (2023) menjadi 92% (2025), dengan dampak positif terukur pada capaian kognitif (effect size d=0,94). Namun, terdapat paradoks kebijakan yang mengkhawatirkan: hanya 19% institusi secara global dan sekitar 20% dari 15 universitas terkemuka di Indonesia yang memiliki regulasi AI formal. Situasi ini semakin kompleks akibat persaingan intensif antara model LLM open source dan closed source yang mereduksi relevansi regulasi berbasis nama alat. Merespons kesenjangan tersebut, penelitian ini mengartikulasikan Kerangka PAIR (Policy–Access–Integrity–Readiness) sebagai panduan strategis untuk mewujudkan adopsi AI yang bertanggung jawab dan kontekstual dalam pendidikan tinggi Indonesia.
Co-Authors Hidayatullah, Muhammad Dimas